How to succeed with business oriented IT projects using business process analysis, use cases and requirements management in general.

Definitions

05/02/2014

Data mining and process mining are some of the concepts that are very hot when talking about big data.

Big data is data that exists everywhere and it is the analysis of these data, that have named a range of techniques - including Data Mining and Process Mining.

Both Data Mining and Process Mining goes under the concept, called Business Intelligence. Business intelligence refers to techniques and tools that are used to analyse large amounts of digital data and retrieve valuable business knowledge out of them. And that is true for data mining techniques as well as process mining techniques - albeit with different perspective on the analysis and the results they produce.

Let's look at some of the similarities between the two :

Both techniques are used to analyse large amounts of data, that it would be impossible to analyse manually

Both techniques produce information that can be used for making business decisions

Both techniques use the "mining" techniques where algorithms traverse through large volumes of data, looking for patterns and relationships

Of course there are some similarities, as both techniques can be categorised as Business Intelligence. But, as mentioned before, the two techniques have different perspectives and goals.

Differences between Data Mining and Process Mining:

Data mining techniques are using multi-dimensional views (cubes ) on data which can be drilled up and down (in different aggregated levels levels). For example, a sale of a product could have the related dimensions: price, product category , customer , region, country , area, day, month, quarter , year, and so on and it is then possible to slice and look at the cube of data and aggregated data in various ways.

Data mining techniques are primarily used to find patterns in large data sets. With data mining techniques it may be possible to find that certain categories of customers demand a certain product, or to find that the customers who most frequently buy product A are also the ones most often buying product B , or that the products placed on a specific location in the shop while running an advertising campaign, are also the ones that sell the best. I remember an English department store which, through data mining techniques, found out that the customers who shopped the most were also those most often buyingt a special Italian cheese that otherwise was not often sold. Traditionally retailers would try to remove products with very low turnover rates and replace them with products with better sales - the problem is that the removal of goods according to the principle could lead to the best customers having to look somewhere else (for the special Italian cheese).

The input to data mining are tables with data

Process mining is not used to find relationship data patterns, but rather to find process relationships in the data. Finding process relationships that provide an overview of processes and activities in the process, and deviations and process performance such as throughput , bottlenecks and discrepancies.

Process mining's perspective is not on patterns in the data but in the processes the data represents.

The goal of process mining is to find information about the business processes

The input to the process mining analysis are event logs , audit trails , and data and events stamped in the IT systems.

Process mining is the " missing link" between data mining and traditional BPM ( Business Process Management ). Data mining provides valuable insights through analysis of data, but is generally not concerned about processes. This is where process mining comes into the picture and gives the opportunity to get the same benefits of data mining ,when working with processes and process improvements.

Process mapping can be done with mining techniques instead of brown -paper workshops and interviews. And the process performance analysis can be made on existing data mining techniques without first collecting data through work studies.

10/06/2011

Don’t you just love buzz words and abbreviations? Abbreviations come in handy in many situations but often confuse people not experienced with business process management.

Some of the most common concepts/abbreviations you will see are the following:

BPM – Business Process Management

BPA – Business Process Analysis

BPMN – Business Process Modeling Language

EA – Enterprise Architecture

BPMS – Business Process Management Suite

BPM is an abbreviation for Business Process Management and refers to the management discipline where the approach is managing the processes. Often BPM is just an umbrella under which you handle various things regarding business processes. Usually when people talk about BPM they refer to AS-IS and TO-BE analysis of processes.

However, analysing your existing processes, documenting the analysis as AS-IS process diagrams and then designing the TO-BE processes is BPA -->Business Process Analysis (notice that BPA is also a part of BPM). Business Process Analysis (BPA) is about analysing the business needs and identify the business process requirements. In BPA the output is process analysis and business requirements – usually the output is captured in process diagrams drawn in modelling tools using for example BPMN as the modelling syntax.

BPMN (Business Process Modeling Notation) is simply a collection of graphical shapes you can use for drawing business process diagrams where the business process diagram is a sequence of business processes connected by control/message directions. Below is shown an example of a process drawn with the BPMN notation. The example is drawn in Microsoft Visio. If you want to draw BPMN diagrams in Visio a Visio BPMN Stencil can be found here (http://www.omg.org/bpmn/documents.htm)

The Visio Stencil contains BPMN figures as shown here:

Enterprise Architecture is a logical structure (architecture) of an enterprise. In enterprise architecture you design how the logical structure and often enterprise architecture is producing logical structural outputs of how the business structure should be – for example using UML structural diagrams such as Class diagrams and component diagrams. Usually enterprise architecture is produced using a modelling tool. In enterprise architecture you design how you business structure should be while in Business Process Analysis you analyse the “problem” and design the business processes”.

BPMS Business Process Management Suite is a suite of applications that can execute your designed business processes. BPMS is both a design-time and run-time environment. In a BPMS you will have a model-driven approach and you will be able to design and orchestrate your business processes and business rules and have them executed in run-time. BPMS is excellent for letting the business drive business changes and BPMS is excellent for workflows especially long workflows (more than 1 hour processing time).

To summarise, as you can see from the figure below the concepts are used for different purposes. When doing Business Process Analysis you are in a conceptual level designing how the processes should be outlined. When moving on to Enterprise Architecture you are on a logical level designing how the structure should be in order to support the conceptual design of business processes. Finally on implementation level you can manage and orchestrate how business processes and business rules are executed. However, please notice that there are some overlap between the various concepts - e.g. requirements are not just captured by one concept alone.

Welcome to All About Requirements. I hope you are visiting because you, just like me, are absolutely passionate about business process analysis, use cases, and requirements in general. Thank you for visiting.
- John